USING GEOGRAPHIC DATA TO STUDY NEAR HIGHWAY POLLUTION AND HEALTH (Invited Presentation)

Motor vehicles release a complex mixture of particulate matter (PM) and gasses in their exhaust. A key component of exhaust that may affect health is the ultrafine particle fraction (UFP) of particles. UFP are the smallest PM, less than 100 nm. This exposure is difficult to study because UFP concentrations vary over small geographic areas (10s of meters) as well as rapidly in time. We conducted two epidemiology studies in the Boston area with the goal of assigning exposure and testing associations with biomarkers of cardiovascular risk. In each study, we used mobile air pollution monitoring and in one, we combined that with stationary monitoring. We used our dense data sets of UFP concentrations to develop predictive statistical models for our study areas over one year in the first case and over many years in the second. We adjusted exposure by participant movement through geographic locations in the first study, which allowed us to improve exposure assessment. We are in the process of adding an additional metric that tests whether short, brief peaks of exposure might have more impact than simple annual average exposures. Both studies found associations with blood pressure and with peripheral blood inflammatory markers, both of which predict risk of heart attacks and strokes. From a geographic perspective, the work presented here shows the critical role that geographic information systems approaches can play in assigning accurate exposures to environmental exposures that exhibit large temporal and special variability. This is because study participants are moving into and out of fields of high exposure so that measured or modeled exposure in one location, usually the residence, is inaccurate. In the absence of the methods we used there is likely substantial exposure measurement error which could reduce or eliminate true associations with health outcomes.